Data Manager/Data Analyst at the Health Complexity Group Department of Public Health

Found in: beBee S DK - 1 month ago

København, Denmark Ku-center For Sundhed og Samfund Full time
Are you a skilled data manager/data analyst? Do you have a passion for building, analysing, and working with large data sets? Are you familiar with the Danish national registries? And do you want to be part of a group of highly dynamic and diverse researchers in the Health Complexity Group? If so, please apply now and join us in making highly relevant research.

We are looking for a motivated and skilled data manager/data analyst who is used to working with large datasets. Your work will involve complex data sets, including nationwide registers. It is a full-time position, starting 15 May 2024, or upon agreement.

The Health Complexity Group

You will be employed in the Health Complexity Group, which aims at building a strong scientific foundation for understanding complex public health problems. The group has recently received a number of larger grants, including an ERC consolidator grant, and is currently expanding and will in the coming years include approx. 20-25 researchers. The Health Complexity Group leverage multi-layered nationwide social and health data combined with an interdisciplinary fusion of methods spanning data science, epidemiology, ethnography, econometrics, and systems science. The group focuses on the complex interplay of health, social, and environmental factors that shape individuals, families, and networks over time. The Health Complexity Group emphasizes interdisciplinary collaboration, offering you the opportunity to actively engage as a collaborative partner in a multitude of projects.

Department of Public Health

The Health Complexity Group is nested within the Department of Public Health. The focus of the Department is to improve the health of the population and the connection between health and society. The Department provides the scientific foundation for efforts that aim to improve public health, both nationally and globally, and to create greater insight into the links between health, the individual, and society. This is achieved through research, education, and engagement with stakeholders and the public at large with a wide-ranging multidisciplinary research agenda covering most aspects of public health at a high international level. You can read more about the Department of Public Health here.

Your job

You will have a supportive and interactive role in data management and data analysis and work in close collaboration with the researchers in the group. The work will primarily include handling the Danish registries and linkage to large cohort studies. Research projects in the group mainly involve life-course registry data across health, social and environmental scales, but can also include data from well-characterized cohort studies.

Most of the work will be carried out through a secure access to the servers at Statistics Denmark using the Department’s research machine: The Public Health Database. You will be working in close collaboration with other data managers at the Public Health Database to update and maintain this important data infrastructure at the Department.

Your main work task will be to expand and maintain the DANLIFE study. DANLIFE is a large register-based study/infrastructure of over 2 million individuals. It involves data from multiple health, social and clinical registers and one of your roles will be to expand it with data on e.g., environmental and neighbourhood factors. You will also be involved in building network structures such as families within DANLIFE by linking individuals to each other via identifiers. The DANLIFE study is used by many researchers and collaborators within and outside the Health Complexity Group, and you will serve as a key contact person for the study.

Another important task will be to structure and prepare a new version of the DANLIFE study that will be placed at the Danish Genome Center. This new version will be created to provide sufficient computer power for advanced machine learning techniques. You will have a key role in structuring and preparing this unique cohort with derived variables and datasets based on FAIR data principles.

You will also be an integral part of the SmartSleep project - a research project about smartphones, sleep, and mental health in adults based on a unique sample of varied data sources including questionnaire data, clinical data, register data and tracking data from smartphones.

You will be able to influence several of your work tasks according to your interests and qualifications and we will support you in developing and learning new approaches relevant to your position, e.g. creating interactive dashboards or integrating GIS and landscape methods to our complexity thinking or whatever qualifications and ideas that may arise through collaboration with the researchers and collaborators in the Health Complexity Group.

Profile and qualifications

We are looking for a highly motivated and enthusiastic data manager / data analyst who, in addition to the desired interests and expertise stated above, has the following skills and qualifications:

a strong expertise in handling national registries, especially the Danish Registries experience in working at a Danish research machine at either Statistics Denmark, the Danish Health Data Authority, or the Genome Center a strong computational background and preferably expertise in dealing with large and complex data sets in either SAS, R, phyton, or related programs an interest in complex systems thinking or a curiosity to learn more about this approach to science extensive experience in analysing data, interpreting results, and concisely summarizing advanced data outputs in an easy and understandable way knowledge of GDPR and data security would be a plus good interpersonal and social skills, fluent in English, both written and spoken a background in epidemiology and public health, natural or data science, biostatistics, machine learning, or any related areas. Your actual background is not that important, more important is, that you are interested in registries and have a helpful and open mindset. Place of employment

The place of employment is the Health Complexity Group, Department of Public Health, University of Copenhagen next to the city lakes in Central Copenhagen.

Terms of employment

The position is a full-time position (37 working hours weekly).
The starting date is May 15st, 2024, or as soon as possible hereafter.

Employment will be in accordance with the provisions of the collective agreement between the Danish Ministry of Taxation and AC (the Danish Confederation of Professional Associations). The monthly salary will be based on the number of years of work experience (seniority) with the possibility to negotiate a salary supplement based on prior experiences and qualifications. The employer will pay an additional 17.1 % to your pension fund.

Questions

For further information regarding the position and the projects, please contact group leader, Professor Naja Hulvej Rod; NAHURO@sund.ku.dk or group coordinator Lise Schmidt; liks@sund.ku.dk. For questions regarding the recruitment procedure, please contact HR at the faculty: SUND-HR-IFSV@sund.ku.dk

Application

Your application can be in either English or Danish and must include the following:

Cover letter, including motivations for applying for this position (max. one page) Curriculum Vitae, including education, work/research experience, language skills and other skills relevant to the position A certified/signed copy of certificate(s) of education Please submit your application by clicking on “Apply Now” below. Only online applications will be accepted.

Application deadline: April 4rd 2024, 23.59 CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

Interviews are expected to be held in week 15.

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

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